BigQuery for Data Engineering
Serverless architecture, partitioning, clustering, costs, UDFs, federated queries, scheduled queries, materialized views
1What storage architecture does BigQuery use?
What storage architecture does BigQuery use?
Answer
BigQuery uses a serverless architecture with columnar storage called Capacitor. This architecture separates storage and compute, enabling independent scaling and separate billing. Columnar storage is optimized for analytical queries as it allows reading only the required columns, significantly reducing I/O.
2What is the main advantage of table partitioning in BigQuery?
What is the main advantage of table partitioning in BigQuery?
Answer
Partitioning divides a large table into smaller segments based on a column (usually a date). During queries, BigQuery can skip irrelevant partitions (partition pruning), reducing the amount of data scanned. This improves performance and reduces costs since BigQuery charges based on the volume of data processed.
3What types of partitioning are available in BigQuery?
What types of partitioning are available in BigQuery?
Answer
BigQuery supports three partitioning types: by DATE or TIMESTAMP column (most common), by integer range (INTEGER RANGE), and by ingestion time (_PARTITIONTIME). Date partitioning is recommended for time-series data as it enables efficient partition pruning on date filters.
What is the difference between partitioning and clustering in BigQuery?
How to optimize query costs in BigQuery?
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